Stroke is a cerebrovascular accident recognized as the leading cause of neurological disability worldwide. Stroke can affect different areas of the brain and, due to death of affected neurological cells, the functionality of specific areas of the brain might be seriously compromised or lost. It has been estimated that among the 75% of stroke survivors, more than half will require specialized rehabilitation. Individuals are left with a broad range of disabilities, from mild paresis to complete paralysis of both the upper and lower extremities. Results from studies exploring the time course of recovery report that approximately 50% of the patients regain some functional abilities in the paretic upper extremity, whereas only 10% to 20% experience complete recovery [Kwak07].
Although neurological cells lose the ability to reproduce soon after the first years of life, there exists a spontaneous recovery process after stroke. A first physiological factor taking place at an early, or acute, phase after stroke is the resolution of the damaged tissue, with a decrease of swelling and bleeding. At the same time, lost functionalities are partly replaced by compensatory behaviors, which allow survivors to keep performing everyday motor tasks, although in an inefficient way. A second physiological factor taking place after stroke but with slower dynamics is phenomenon of plasticity. Despite the death of specific neurological cells, their function can be dynamically reallocated thanks to a diffuse and redundant network connecting different areas of the brain. The plasticity is an ongoing phenomenon since birth but it is enhanced soon after stroke and is strongly affected by the environment and “experience-associated neural changes have the potential to either hinder or enhance functional recovery” [Sch00].
The principle that plasticity is induced by motor practice, both active and passive, has inspired several neuro-rehabilitation techniques. However, the optimal training strategy for facilitating plasticity and functional reorganization has remained unclear thus far. One of the main reasons is that dose and consistency of therapy delivered by a therapist and outcomes as assessed via available clinical scales can be hardly compared across therapists. In this sense, robotic devices emerged as an objective means to deliver therapy and measure outcomes. Another reason is also due to the limited amount of therapy which a stroke survivor can be exposed to, exacerbated by an aging population, cost of health-care/therapy and insurance policies.
In this regard, rehabilitation robots have been developed to alleviate the burden on therapists and healthcare systems, while simultaneously increasing patient access to rehabilitation. Several studies have shown similar improvement in stroke survivor outcomes with the use of rehabilitation robotic devices when compared with conventional therapy. Robot-aided therapy complements conventional therapy with features such as exact repetitive movements, programmable resistance/assistance levels, objective evaluation, and motion sensing capabilities. Robots also represent a potential aid for therapists to extend rehabilitation to remote locations or to a patient's home.
Active participation to the therapy can be enhanced by virtual reality environments, where the concomitance of haptic and visual stimuli further increase the so-called Hebbian learning processes behind plasticity. In addition to this, robotic devices can accurately measure kinematic (e.g. position, speed) and dynamic (interaction forces) parameters, providing fine and objective assessment which complements the available clinical scales, such as the Fugl-Meyer, Wolf Motor Function, Stroke Impact Scale.
Many robotic devices have been developed which target post-stroke rehabilitation of the upper-limb [Bre07], however very few are commercially available and, in any case, their use in hospitals and clinics is still very limited due to high costs and complexity.
At the moment, the only commercially available robots for elbow/shoulder rehabilitation are shown in FIG. 1. Other robots only exist as research prototypes, e.g [Gurg00], [Lum02], [Mice05], [Rein00], [Kre98], [Vol00], and have been used in clinical studies to validate their efficacy in rehabilitation. Sample sizes used in initial, pilot studies to prove clinical usefulness (for some robots more than two studies are available) are shown in FIG. 2. Among these, only four devices are of 2D planar, end-effector type, namely MIT-MANUS [Kre98], Braccio-di-Ferro [Casa09], MEMOS [Mice05], and Reha-Slide [Hess08]. Only the first three are in fact robots (as they entail actuation) while the Reha-slide is passive machine, as described later.
As shown in FIGS. 3(a) and 3(c) respectively, MIT-MANUS [Kre98] and Braccio-di-Ferro [Casa09] are functionally very similar. Meant for rehabilitation of the shoulder and elbow, both robots are based on the so-called pantographic mechanism (FIG. 3(b)) which ensures a so-called low intrinsic end-point impedance due to the very low inertia and friction properties of the mechanism, while able to impose large forces at the handle (up to 5 kg of continuous force). These characteristics allow both the MIT-MANUS and Braccio-di-Ferro to rapidly comply with the subject's movements. Both robots are also endowed with sensors which allow measuring the position and velocity of the handle as well as interaction forces between robot and patient. During the therapy, the subject's arm is attached to the end-effector (handle) of the robot. The subject moves the handle and performs goal-directed tasks, such as reaching a target, often guided by a videogame. The robots senses the current position and velocity (e.g. direction) of the reaching movement and is capable of exerting assistive or disturbing forces, or more general force fields, according to the therapy to be imparted. From a clinical evaluation perspective, the MIT-MANUS is the only commercially available robot in this category and also the most clinically studied device for upper-limb neuro-rehabilitation. Many random controlled trials (RCT) have shown statistically significant decrease of impairment, at the level of shoulder and elbow, for acute, sub-acute as well as chronic stroke survivors. These studies were performed on sample sizes which varied from twenty to one hundred and twenty seven subjects. A recent, multi-centre RCT study involving one hundred and twenty seven patients, showed that robot-assisted therapy was no better than usual therapy and intensive therapy after 12 weeks but that it was better than usual therapy after three months [Lo10].
Unfortunately, the MIT-MANUS and Braccio-di-Ferro robots (and similar devices) share the following drawbacks:                lack of portability, limiting the potential use at home or community centres;        high complexity, requiring highly trained personnel (to ensure safe operations as well); and        high costs, meaning that only few and specialized clinics can afford (at most) one, thus limiting their availability to most of impaired subjects, especially those with mild impairments.        
Referring to FIG. 4, the MEMOS [Mice05], ARM guide [Rein00] and the Reha-Slide [Hess08] are examples of two planar devices for neuro-rehabilitation of the shoulder/elbow meant to represent a trade-off between the best clinical efficacy and the least amount of robotic complexity. The Reha-Slide device, in fact, is not a robot but a lower cost passive machine designed for bi-manual arm training. The Reha-Slide is a one degree-of-freedom passive device whereby the patient uses the unaffected arm to aid the affected one, exercising the shoulder, elbow, and wrist. In a multi-centre RCT study, fifty-four sub-acute stroke survivors, over a six week period, received therapy with the Reha-Slide or electrical stimulation in addition to standard care. Significant improvement was found in both groups but no statistically significant difference [Hess08].
The ARM guide robot was designed to assess multi-joint coordination during fundamental to many activities of daily living such as reaching tasks. As reaching movements in healthy subjects are known to approximately follow straight-line trajectories, a passive, linear constraint with a single motor robot was used to assist in arm movement and to reduce complexity and costs typical of multi-degrees-of-freedom robots [Rein00]. A RCT study including nineteen patients showed that the therapy based on the ARM guide robot improved arm movement ability, although no difference was detectable with a group performing task-matched unassisted reaching tasks.
Unlike the ARM guide and the Reha-Slide, the MEMOS robot is based on a 2D planar mechanism in a Cartesian configuration. While this simplifies the kinematics and therefore the control, the issue with the MEMOS is that it simply readapts industrial robots design. Industrial robots, well known to be repeatable, implement position-controlled architectures, not suitable for the flexibility required for interacting with humans, whether healthy or impaired. Such flexibility can be achieved by means of admittance control, whereby force sensors are used to sense the human reaction forces and command appropriate actions. However, this approach has several limitations. Firstly, it relies on force sensors, typically expensive and noisy, making the system insensible to weak interactions. Secondly, in order to adapt quickly to changes of interaction forces, large motors should be used, making the system intrinsically unsafe for humans and exceedingly expensive. The inertia and friction of mechanisms, as perceived by the user, are typically high and cannot be sufficiently compensated for by means of active control. This is clearly an issue in rehabilitation as subject's movements are strongly influenced by the mechanical impedance of the robot [Cam09] while ‘assist-as-needed’ strategies are fundamental for increasing recovery.